Philip J. Murphy

Dr. Murphy earned his PhD in Public and International Affairs from the University of Pittsburgh, where he recently held the position of Senior Policy Fellow at the Matthew B. Ridgway Center for International Security Studies. He has taught distance education courses in a Master of Public Policy and Management program targeted at mid-career public and private sector professionals in Macedonia. He has also been an Adjunct Professor at the Graduate School of Public and International Affairs and a visiting faculty member in the Faculty of Public Administration at South East European University, a university in Macedonia that is dedicated to increasing ethnic inclusion and improving the quality of the country’s public higher education.

His research interests include the application and advancement of innovative methods for detecting and discerning “dark” networks and other difficult to identify social, identity, or interest groups. He is particularly interested in the ideas of distributed cognition and shared identity (i.e., shared perceptions, overlapping frames of reference). The ability to identify – or perhaps promote – shared identities in a population, especially those that bridge disparate religious and ethno-cultural communities, holds great promise for enhancing policymaking, increasing stability, and implementing policy in developing and divided societies. He is currently involved in research projects in the fields of network analysis, public health, and security studies.

Expertise

Public Policy, Research Methods, Quantitative Methods, Network Analysis, International Development

Education

Ph.D University of Pittsburgh; MA East Tennessee State University; BS Appalachian State University

Selected Publications

"Knowledge Hub and Inventory of Opportunities."

"Getting it Done: A Brief Overview of Critical Junctures in the Study of How Policy Translates into Practice."

"Models, Methods, and Stereotypes: Efforts to Maintain, Reify, and Create Macedonia's Ethnopolitical Identities and how Research can Move beyond Them."

"Public Policy Analysis and its Importance to Public Administration Reform."

Course List

Courses offered in the past four years. ▲indicates offered in the current term▹indicates offered in the upcoming term[s]

DPPG 8500 - Intro to Policy & DataAnalysis
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This course is a guided introduction to conceptualizing problems and making sense of quantitative information in the policy sphere. The course begins by introducing the theory and practice of policy analysis. The stages of the public policy process and methods for structuring policy inquiry are introduced to provide a means for deconstructing policy problems and asking relevant and practical questions in a policy context.

Next the class is introduced to how such questions are addressed using quantitative tools. Topics to be covered include sampling, estimation, hypothesis testing, analysis of variance, and regression techniques. This will basically be a primer on applying inferential statistics to policy problems. The course will also include introductory training in the use of innovative statistical software, as well as Excel statistical functions.

DPPG 8609 - Field Methods
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This course is the first in a series of three steps that provides the instruction and experience in conducting and analyzing field research as part of a dedicated research team. Anyone planning to run or collaborate in a field research project would benefit from the opportunity to take part in a functioning research team.

The Fieldwork course follows Introduction to Policy and Data Analysis and focuses on preparing the tools that will be used in the field to gather information that is relevant to a particular research program. In each case, groups within this class will work with a client in the country or region to design and train in the use of tools that to address the client’s needs.

The course covers the design and construction of surveys, semi-structured interviews, and focus groups, as well as how to design sampling strategies for each. Course participants will design working versions of at least two of these tools and prepare them for use in the field. The tools that come out of this course will be the ones that are used when groups go into the field on their J-Term practica.

IPMG 9532 - Peru Practicum

IPSG 8501 - Policy Analysis

This course introduces students to the theory and practice of policy analysis. Students will be introduced to the stages of the public policy process, including agenda setting, formulation, implementation, and evaluation. Students will also develop basic policy analysis skills, including problem structuring, stakeholder identification, summarization of current policy, development of policy options, elaboration of criteria for selection, and recommendation of course of action. These concepts are illustrated by examples policies that fall within students' range of interests. This course also introduces students to scientific methods that are used as a means for structuring policy inquiry. A series of research approaches and techniques are presented in the context of forecasting, monitoring, and evaluation for the analysis of domestic and international policies.

IPSG 8504 - Data Analysis for Public Polcy

The course is an introduction to inferential statistics with an emphasis on Policy Analysis applications. Topics to be covered include sampling, estimation, hypothesis testing, analysis of variance, and simple and multiple regression analysis. The course will also include an introduction to the use of the computer as a tool for data analysis using leading statistical packages, as well as Excel statistical functions.

IPSG 8532 - Peru Practicum

IPSG 8565 - Intro to Network Analysis

This course introduces students to the skills and concepts at the core of a dynamic and rapidly developing interdisciplinary field. Network analytic tools focus on the relationships between nodes (e.g., individuals, groups, organizations, countries, etc.). We analyze these relationships to uncover or predict a variety of important factors (e.g., the potential or importance of various actors, organizational vulnerabilities, potential subgroups, the need for redundancy, social and economic ties, growth within a network, …). Although the security field has received the greatest amount of recent attention (covert or terrorist networks), these tools can offer valuable insight into a variety of disciplines. The combination of – often stunning – visual analytic techniques with more quantitative measures accounts for much of the increasing worldwide popularity of this field.

Course Objectives

At the end of the semester, students will be able to:
Explain and apply a number of the concepts that underpin network analysis Apply concepts such as centrality, brokerage, equivalence and diffusion to network data Critically evaluate structures and substructures within a network Perform a variety of approaches to clustering and cohesion to networks Analyze networks using a variety of software packages

IPSG 8673 - Advanced Data Analysis

The advanced data analysis course was designed to provide students with the opportunity to expand upon the skills developed in the introductory course (IPSG 8504), and introduce new skills that address a greater range of analytic needs. This is a project-based, applied course. Class discussions will include both how and why to use these tools, with a strong emphasis on policy applications. Among others, the course covers modules on Factor Analysis, Non-Linear Regression, Spatial Analysis and Time Series Analysis, and its design has a strong emphasis on policy applications. Multiple data sets will be used, but students are encouraged to use their own data and background knowledge.

IPSG 9507 - QualitativeDataAnalysisMash-Up

This lively, hands-on course focuses on analysis of qualitative data. By “data”, we mean interview, focus group, written reports and visual records, hundreds of pages of them. Students will have a choice of qualitative data sets – there is no time in this short course to engage in primary data collection -- and our entire focus will be on a) deciding how to interrogate the data (what is it you wish to know, demonstrate, reveal, test?), b) developing code books and coding, c) inter-coder reliability, and d) a wide variety of analytical approaches you can use, once you have qualitative data reduced and organized. The first seven weeks of the course focus on a-c. Then, during a final weekend workshop, students will engage in hands-on analysis, using techniques introduced rapid fire during the workshop: expect to practice no fewer than 20 qualitative analysis techniques over three days. This course emphasizes the importance of studying/reading high quality qualitative research studies as fundamental to learning – we will dissect one study each week to understand how the researchers put it together – while also emphasizing learning-through-doing, making mistakes, and collaborative analysis (qualitative inquiry is almost always improved through collaboration). Your final product will be a 10-page analysis, due two weeks after the final workshop.

MPAG 8507 - QualitativeDataAnalysisMash-Up

This lively, hands-on course focuses on analysis of qualitative data. By “data”, we mean interview, focus group, written reports and visual records, hundreds of pages of them. Students will have a choice of qualitative data sets – there is no time in this short course to engage in primary data collection -- and our entire focus will be on a) deciding how to interrogate the data (what is it you wish to know, demonstrate, reveal, test?), b) developing code books and coding, c) inter-coder reliability, and d) a wide variety of analytical approaches you can use, once you have qualitative data reduced and organized. The first seven weeks of the course focus on a-c. Then, during a final weekend workshop, students will engage in hands-on analysis, using techniques introduced rapid fire during the workshop: expect to practice no fewer than 20 qualitative analysis techniques over three days. This course emphasizes the importance of studying/reading high quality qualitative research studies as fundamental to learning – we will dissect one study each week to understand how the researchers put it together – while also emphasizing learning-through-doing, making mistakes, and collaborative analysis (qualitative inquiry is almost always improved through collaboration). Your final product will be a 10-page analysis, due two weeks after the final workshop.